
'''simple docstring'''

import argparse
import copy







def 	A  (   UpperCamelCase_       :  str   )       ->							Union[str, Any]:







			'''simple docstring'''



			lowerCAmelCase__										=				{}

			with open(UpperCamelCase_   ) as f:
						for line in f:
									if line.split()[0] not in dict_of_neighbours:
												lowerCAmelCase__										=				[]
												_list.append([line.split()[1], line.split()[2]]   )
												lowerCAmelCase__										=				_list
									else:
												dict_of_neighbours[line.split()[0]].append(
												    [line.split()[1], line.split()[2]]   )
									if line.split()[1] not in dict_of_neighbours:
												lowerCAmelCase__										=				[]
												_list.append([line.split()[0], line.split()[2]]   )
												lowerCAmelCase__										=				_list
									else:
												dict_of_neighbours[line.split()[1]].append(
												    [line.split()[0], line.split()[2]]   )

			return dict_of_neighbours







def 	A  (   UpperCamelCase_       :  Optional[Any]    ,						UpperCamelCase_       :  str   )       ->							List[str]:







			'''simple docstring'''



			with open(UpperCamelCase_   ) as f:
						lowerCAmelCase__										=				f.read(1   )
			lowerCAmelCase__										=				start_node

			lowerCAmelCase__										=				[]

			lowerCAmelCase__										=				start_node

			lowerCAmelCase__										=				0
			while visiting not in first_solution:
						lowerCAmelCase__										=				1_00_00
						for k in dict_of_neighbours[visiting]:
									if int(k[1]   ) < int(UpperCamelCase_   ) and k[0] not in first_solution:
												lowerCAmelCase__										=				k[1]
												lowerCAmelCase__										=				k[0]

						first_solution.append(UpperCamelCase_   )
						lowerCAmelCase__										=				distance_of_first_solution + int(UpperCamelCase_   )
						lowerCAmelCase__										=				best_node

			first_solution.append(UpperCamelCase_   )

			lowerCAmelCase__										=				0
			for k in dict_of_neighbours[first_solution[-2]]:
						if k[0] == start_node:
									break
						position += 1

			lowerCAmelCase__										=				(
			    distance_of_first_solution
			    + int(dict_of_neighbours[first_solution[-2]][position][1]   )
			    - 1_00_00
			)
			return first_solution, distance_of_first_solution







def 	A  (   UpperCamelCase_       :  str    ,						UpperCamelCase_       :  Dict   )       ->							Dict:







			'''simple docstring'''



			lowerCAmelCase__										=				[]

			for n in solution[1:-1]:
						lowerCAmelCase__										=				solution.index(UpperCamelCase_   )
						for kn in solution[1:-1]:
									lowerCAmelCase__										=				solution.index(UpperCamelCase_   )
									if n == kn:
												continue

									lowerCAmelCase__										=				copy.deepcopy(UpperCamelCase_   )
									lowerCAmelCase__										=				kn
									lowerCAmelCase__										=				n

									lowerCAmelCase__										=				0

									for k in _tmp[:-1]:
												lowerCAmelCase__										=				_tmp[_tmp.index(UpperCamelCase_   ) + 1]
												for i in dict_of_neighbours[k]:
															if i[0] == next_node:
																		lowerCAmelCase__										=				distance + int(i[1]   )
									_tmp.append(UpperCamelCase_   )

									if _tmp not in neighborhood_of_solution:
												neighborhood_of_solution.append(_tmp   )

			lowerCAmelCase__										=				len(neighborhood_of_solution[0]   ) - 1

			neighborhood_of_solution.sort(key=lambda UpperCamelCase_   : x[index_of_last_item_in_the_list]   )
			return neighborhood_of_solution







def 	A  (   UpperCamelCase_       :  Dict    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  str    ,						UpperCamelCase_       :  Dict    ,						UpperCamelCase_       :  Tuple   )       ->							Dict:







			'''simple docstring'''



			lowerCAmelCase__										=				1
			lowerCAmelCase__										=				first_solution
			lowerCAmelCase__										=				[]
			lowerCAmelCase__										=				distance_of_first_solution
			lowerCAmelCase__										=				solution

			while count <= iters:
						lowerCAmelCase__										=				find_neighborhood(UpperCamelCase_    ,						UpperCamelCase_   )
						lowerCAmelCase__										=				0
						lowerCAmelCase__										=				neighborhood[index_of_best_solution]
						lowerCAmelCase__										=				len(UpperCamelCase_   ) - 1

						lowerCAmelCase__										=				False
						while not found:
									lowerCAmelCase__										=				0
									while i < len(UpperCamelCase_   ):
												if best_solution[i] != solution[i]:
															lowerCAmelCase__										=				best_solution[i]
															lowerCAmelCase__										=				solution[i]
															break
												lowerCAmelCase__										=				i + 1

									if [first_exchange_node, second_exchange_node] not in tabu_list and [
									    second_exchange_node,
									    first_exchange_node,
									] not in tabu_list:
												tabu_list.append([first_exchange_node, second_exchange_node]   )
												lowerCAmelCase__										=				True
												lowerCAmelCase__										=				best_solution[:-1]
												lowerCAmelCase__										=				neighborhood[index_of_best_solution][best_cost_index]
												if cost < best_cost:
															lowerCAmelCase__										=				cost
															lowerCAmelCase__										=				solution
									else:
												lowerCAmelCase__										=				index_of_best_solution + 1
												lowerCAmelCase__										=				neighborhood[index_of_best_solution]

						if len(UpperCamelCase_   ) >= size:
									tabu_list.pop(0   )

						lowerCAmelCase__										=				count + 1

			return best_solution_ever, best_cost







def 	A  (   UpperCamelCase_       :  Optional[int]=None   )       ->							Union[str, Any]:







			'''simple docstring'''



			lowerCAmelCase__										=				generate_neighbours(args.File   )

			lowerCAmelCase__						,lowerCAmelCase__										=				generate_first_solution(
			    args.File    ,						UpperCamelCase_   )

			lowerCAmelCase__						,lowerCAmelCase__										=				tabu_search(
			    UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						args.Iterations    ,						args.Size    ,						)

			print(F"""Best solution: {best_sol}, with total distance: {best_cost}."""   )


if __name__ == "__main__":
		UpperCAmelCase__ :			Optional[Any]											=		argparse.ArgumentParser(description="Tabu Search")
		parser.add_argument(
		    "-f",
		    "--File",
		    type=str,
		    help="Path to the file containing the data",
		    required=True,
		)
		parser.add_argument(
		    "-i",
		    "--Iterations",
		    type=int,
		    help="How many iterations the algorithm should perform",
		    required=True,
		)
		parser.add_argument(
		    "-s", "--Size", type=int, help="Size of the tabu list", required=True
		)

		# Pass the arguments to main method
		main(parser.parse_args())









"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowercase_							=							{
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							=							['LayoutLMv2TokenizerFast']

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							=							['LayoutLMv2FeatureExtractor']
		lowercase_							=							['LayoutLMv2ImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							=							[
		    'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'LayoutLMv2ForQuestionAnswering',
		    'LayoutLMv2ForSequenceClassification',
		    'LayoutLMv2ForTokenClassification',
		    'LayoutLMv2Layer',
		    'LayoutLMv2Model',
		    'LayoutLMv2PreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
		from .processing_layoutlmva import LayoutLMvaProcessor
		from .tokenization_layoutlmva import LayoutLMvaTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_layoutlmva import (
				    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LayoutLMvaForQuestionAnswering,
				    LayoutLMvaForSequenceClassification,
				    LayoutLMvaForTokenClassification,
				    LayoutLMvaLayer,
				    LayoutLMvaModel,
				    LayoutLMvaPreTrainedModel,
				)
else:
		import sys

		lowercase_							=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)